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SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 1/20 Level 2 Ocean Salinity 16-17 May 2013 OTT post-processor.

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Presentation on theme: "SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 1/20 Level 2 Ocean Salinity 16-17 May 2013 OTT post-processor."— Presentation transcript:

1 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 1/20 Level 2 Ocean Salinity 16-17 May 2013 OTT post-processor

2 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 2/20 Real-time salinity retrieval requires near real-time OTT to track short term drift: while processing L1c, L2OS v610 extracts deltaTBs for South Pacific region and writes them to AUX_DTBXY. The OSCOTT runs once per day (TBC), reads AUX_DTBXY and a set of current deltaTBs (from AUX_DTBCUR), writes a new set of OTTs, and updates AUX_DTBCUR. deltaTBs (DTBXY_) current deltaTBs (DTBCUR) OTT post- processor OTTs L2OS processor L1c L2OS UDP & DAP OTT post-processor (OSCOTT)

3 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 3/20 Previously the ARGANS OTT tool chain (compareTBs, Python scripts) extracted deltaTBs for South Pacific (typically 3x8x12M = 288M per orbit) and constructed OTT by interpolating measurements onto a 129x129 xi/eta rectangular grid. To avoid very large intermediate files, L2OS v610 will write deltaTBs binned on a 129x129 grid (5M per orbit) using a non-square xi/eta interpolation grid ±0.7 in xi, -0.7 to + 0.4 in eta (previously ±0.7 in xi & eta: large areas in each LUT were unused). No changes to AUX_OTTxF/D schema. AUX_DTBXY_ contains deltaTB data for each of the 3 models, and for each of the 8 polarisations (HH, VV, HHV real, HHV imag, VVH real, VVH imag, HH short, VV short). OSCOTT will merge AUX_DTBXY data to make OTT1/2/3 (each OTT contains 8 LUTs for ascending, & 8 LUTs for descending orbits). OTT post-processor overview

4 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 4/20 for each selected measurement map xi,eta onto x,y grid count[x,y] += 1 sumDeltaTB[x,y] += TBsmos – Tbmodel sumDeltaRA[x,y] += (TBsmos – Tbmodel) / ra sumDeltaRA2[x,y] += ((TBsmos – Tbmodel) / ra) 2 flags[x,y] |= selected L1c & L2OS flags for x = 0 to 128 for y = 0 to 128 n = count[x,y] write n mean_deltaTB[x,y] = sumDeltaTB[x,y] / n write mean_deltaTB[x,y] stdra[x,y] = sqrt(((n * sumDeltaRA2[x,y] – sumDeltaRA[x,y] 2 ) / (n * (n – 1))) write stdra[x,y] write flags[x,y] OTT post-processor: L2OS algorithm AUX_DTBXY count[x,y] deltaTB[x,y] stdra[x,y] flags[x,y] Statistics for fov, affov, eaffov, & filtered by L1 flags Flags allow for off-line analysis:

5 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 5/20 OTT post-processor components: AUX_DTBXY n x regions: ID snapshot start/stop times snapshot start/stop ID for 3 models for 8 polarisations 4 x statistics count[x,y] deltaTB[x,y] stdra[x,y] flags[x,y] AUX_DTBXY_ datablock Statistics for FOV, AFFOV, EAFFOV, & filtered by flags[x,y}; min, max, mean, median, std Any number of regions can be defined in AUX_CNFOSF (but v610 OSCOTT will only use South Pacific to make OTTs). Could be useful for drift monitoring...

6 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 6/20 Header contains quality information, used by OSCOTT to select ‘good’ sets of deltaTBs: OTT post-processor components: AUX_DTBXY Grid point quality information total grid points in region number of grid points used after filtering (configurable via ADF) number of grid points: too near to land/coast rain/ice contamination missing ECMWF data WS 7m/s Measurement quality information total measurements in region number of measurements used after filtering (configurable via ADF) number of measurements flagged: as sun point, sun tails with sun/moon/galactic glint contaminated by RFI (by L1 or L2) L1 processing error Quality information is from forward model 1 only. Criteria for ‘good’ deltaTBs TBD.

7 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 7/20 Which statistics should be used to select/reject DTBXY deltaTB data? Grid point & measurement selection statistics? 2012 OTTs Ascending Descending

8 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 8/20 Which statistics should be used to select/reject DTBXY deltaTB data? Grid point & measurement selection statistics? 2012 OTTs Ascending Descending

9 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 9/20 Other statistics available: %RFI, %L1c degraded (eg missing VTEC). 2012 OTTs Ascending Descending

10 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 10/20 OTT post-processor: quality selection criteria Which statistics should be used to select/reject DTBXY deltaTB data? v600 OTT for 20110501T014022 (v600 statistics are after binning measurements) deltaTBstdra

11 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 11/20 Which statistics should be used to select/reject DTBXY deltaTB data? v610 OTT for 20110501T014022 Put threshold on sigma(std)? OTT post-processor: quality selection criteria AF: mean = -0.09 min = -4.0 max = 6.6 σ = 1.5 EAF: mean = 0.48 min = -16.1 max = 46.7 σ = 4.4 A+EAF: mean = 0.22 min = -16.1 max = 46.7 σ = 3.4 AF: mean = 1.33 min = 0.0 max = 4.0 σ = 0.50 EAF: mean = 1.14 min = 0.0 max = 4.9 σ = 0.41 A+EAF: mean = 1.22 min = 0.0 max = 4.9 σ = 0.46 SM_TEST_AUX_DTBXY__20110501T014022_20110501T023334_606_001_8

12 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 12/20 OTT post-processor: comparing AUX_DTBXY v600 Transect at xi=0 (single bin) v610

13 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 13/20 OTT post-processor components: AUX_DTBCUR n x regions: ID snapshot start/stop times snapshot start/stop ID for 3 models for 8 polarisations 4 x statistics count[x,y] deltaTB[x,y] stdra[x,y] flags[x,y] AUX_DTBXY_ datablock m x AUX_DTBXY + extra sets: set type (L1c, mean...) region ID orbit direction (A/D) snapshot start/stop times snapshot start/stop ID filename for 3 models for 8 polarisations 4 x statistics count[x,y] deltaTB[x,y] stdra[x,y] flags[x,y] AUX_DTBCUR datablock OSCOTT v610 OSCOTT will only process South Pacific orbits into OTT m x AUX_DTBXY

14 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 14/20 orbits = read input AUX_DTBCUR orbit = read each AUX_DTBXY if region ID = South Pacific & good quality orbits += orbit for dir = A, D // orbit direction discard orbits input validity start = input AUX_DTBCUR output validity start = mean snapshot time(orbits) if (input validity start < output validity start) for model = 1 to 3 compute OTT(model) from orbits write OTT(model) write orbits to new AUX_DTBCUR OSCOTT preliminary algorithm Alternative orbit discarding algorithms: // fixed number of orbits, time varying while count(orbits(dir)) > max orbits discard oldest orbit // fixed window of n days for orbit in orbits if date(orbit) < max days discard orbit Alternative OTT computation algorithms: mean or weighted mean? separate spatial biases & drift multi-region

15 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 15/20 for orbit in orbits for x = 0 to 128 for y = 0 to 128 n = orbit.count[x,y] count [x,y ] += n sum[x,y] += orbit.deltaTB[x,y] * n for x = 0 to 128 for y = 0 to 128 ott.deltaTB [x,y] = sum[x,y] / count [x,y] Could use stdra[x,y] too? OTT post-processor weighted merging

16 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 16/20 20110501T123046 20110501T141049 20110502T133154 20110503T125255 20110503T143301 20110504T135404 20110505T131507 20110505T145617 20110506T123611 20110506T141615 OTT post-processor sample run Job run timeInputsOutputs 20110502T010000AUX_DTBCUR_20050101T000000 AUX_DTBCUR_20110501T073358 AUX_DTBXY__20110501T123046 AUX_OTT1F__20110501T073358 AUX_DTBXY__20110501T141049 AUX_OTT2F__20110501T073358 AUX_DTBXY__20110501T000016 AUX_OTT3F__20110501T073358 AUX_DTBXY__20110501T014022 20110503T010000AUX_DTBCUR_20110501T073358 AUX_DTBCUR_20110501T191436 AUX_DTBXY__20110502T133154 AUX_OTT1F__20110501T191436 AUX_DTBXY__20110502T010125 AUX_OTT2F__20110501T191436 AUX_OTT3F__20110501T191436 20110501T000016 20110501T014022 20110502T010125 20110503T002227 20110503T020232 20110503T234330 20110504T012337 20110506T000541 20110506T014547 20110507T010650 Output product validity start is mean time of all snapshots used to make OTT (& written to DTBCUR) OSCOTT first run can be without an empty AUX_DTBCUR

17 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 17/20 OTT post-processor orchestration DPGS could run OSCOTT once per day with all new AUX_DTBXY from previous day For reprocessing the required speed increase is x18, and a run of L2OS takes 4 hours max, so ESA propose to run OSCOTT each time 3 days of DTBXY are available. Do we want DPGS to run OSCOTT once per day (ie different from foreseen reprocessing), or once every 3 days?

18 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 18/20 OTT interpolation Prior to v610, L2OS performed nearest neighbour interpolation when applying OTT LUTs to correct L1c TBs. But we see ±1K jumps between xi/eta cells in OTT: Maybe we should perform 2D interpolation in v610?

19 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 19/20 DTBXY grid resolution What resolution is best for AUX_DTBXY? Grid point density varies within snapshot – highest at leading edge of AFFOV Typical total 5600 grid points, >100 along leading edge (±0.25 xi) x2 oversampling suggests >600 for xi ±0.75

20 SMOS L2 Ocean Salinity – PM#25 www.argans.co.uk/smos 20/20 Drift statistics AUX_DTBCUR header could/should contain summary deltaTBs for OTT generated from the set of deltaTBs in the AUX_DTBCUR datablock. Which are useful for monitoring? For deltaTB[x,y] and stdra[x,y] min, max, mean, median, std for all of FOV (excluding border) AFFOV (excluding border) EAFFOV (excluding border) filtered by AFFOV, border, sun point/tails Other?


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